Optimization of Communication Base Station Battery Configuration Considering Demand Transfer and Sleep Mechanism under Uncertain Interruption Duration

In the communication power supply field, base station interruptions may occur due to sudden natural disasters or unstable power supplies. This work studies the optimization of battery resource configurations to cope with the duration uncertainty of base station interruption. We mainly consider the demand transfer and sleep mechanism of the base station and establish a two-stage stochastic programming model to minimize battery configuration costs and operational costs. To transform the uncertainty expression in the first stage into a deterministic model, we design the K-Means-SAA algorithm to accelerate problem-solving and to compare it with the SAA algorithm. The case study results indicate that the proposed two-stage stochastic programming model can save 17.02% of the total cost compared to the expected value model. The proposed demand transfer and sleep mechanism can reduce the total cost by 41.92% compared to no mechanism. The results of numerical experiments and sensitivity analysis also verify the superiority of the designed algorithm in terms of running efficiency and solving time. Therefore, the model and algorithm proposed in this work provide valuable application guidance for large-scale base station configuration optimization of battery resources to cope with interruptions in practical scenarios.